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3rd International Workshop on Information Technologies: Theoretical and Applied Problems, ITTAP 2023

作者： Lupenko, Serhii Butsiy, Roman Volyanyk, Oleksandr Stadnyk, Nataliia Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole45-758 Poland Institute of Telecommunications and Global Information Space National Academy of Sciences of Ukraine Kyiv02000 Ukraine Ternopil Ivan Puluj National Technical University Ternopil46001 Ukraine

This study provides a comprehensive assessment of an extended set of modern classifiers designed for electroencephalography signal analysis in brain-computer interface systems. Using the modern model of the vector of cyclic rhythmically connected random processes for estimating signal characteristics, the classifiers compared encompass k-NN, Linear SVM, Decision Tree, Random Forest, Multilayer Perceptron, AdaBoost, and Naive Bayes. By decomposing signals into Fourier series, the optimal number of coefficients is investigated to both reduce computational complexity and increase accuracy. To facilitate a transparent and decisive comparison among the classifiers, the Confusion Matrix methodology is used. Results suggest that among the diverse range evaluated, Linear SVM, Naive Bayes, and Multilayer Perceptron classifiers showcased superior accuracy. © 2023 CEUR-WS. All rights reserved.

关键词： Brain computer interface

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Network Management devices in an SDN environment

Network Management devices in an SDN environment

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International Conference on control Systems and computer Science (CSCS)

作者： Diyar Jamal Hamad Khirota Gorgees Yalda Nicolae Tapus Ibrahim Taner Okumus Faculty of Automatic Control and Computer Science Politehnica University of Bucharest Bucharest Romania Soran Technical college Erbil Polytechnic University Iraq Erbil Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey

Network optimization and continued availability depend on a number of capabilities that are part of network management. The Maintenance, operating and also offering a safeguarded interaction network is very complicated. It calls for the network operators to grapple with low-level vendor particular arrangements to execute the high degree network policies which are complicated. A method for monitoring networks with OpenFlow controller is presented in this paper in two separate functions for the same networks. Bandwidth utilization, Meter values, charts and statistics are provided by the method to extend controller monitoring capabilities. The method architecture and implementation will be introduced in order to present the feature set. Additionally, softswitches are used as a switch and Mininet to evaluate a virtualized network. This analysis shows whether Meters or ports value is better for network management.

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Post-Processing of Thresholding or Deep Learning Methods for Enhanced Tissue Segmentation of Whole-Slide Histopathological Images

Post-Processing of Thresholding or Deep Learning Methods for...

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18th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2025

作者： Marczyk, Michal Wrobel, Agata Merta, Julia Polanska, Joanna Department of Data Science and Engineering Silesian University of Technology Gliwice44-100 Poland Yale Cancer Center Yale School of Medicine New HavenCT06511 United States Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland

Digital pathology allows for the efficient storage and advanced computational analysis of stained histopathological slides of various tissues. Tissue segmentation is a crucial first step of digital pathology aimed at eliminating background, pen markings, and other artifacts, reducing image size, and increasing the efficiency of further analysis. In most cases, color thresholding or deep learning models are used, but their effectiveness is reduced due to complex artifacts and huge color variations between slides. We propose a post processing method to increase the tissue segmentation performance of any initial segmentation algorithm. Using a set of 197 manually annotated histopathological images of breast cancer patients and 63 images of endometrial cancer patients, we tested our method with 3 thresholding techniques and 3 deep learning-based algorithms by calculating the Dice index, Jaccard index, precision, and recall. In both datasets, applying post processing increased precision and recall for thresholding methods and mostly precision for deep learning models. Overall, applying post-processing gave better tissue segmentation performance than initial segmentation methods, significantly increasing Dice and Jaccard indices. Our results proved that thanks to post-processing, the tissue segmentation pipeline is more robust to noises and artifacts commonly present in histopathological images. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Image segmentation

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A Survey on Security Issues in Cloud Systems

A Survey on Security Issues in Cloud Systems

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Roedunet International Conference (RoEduNet)

作者： Diyar Jamal Hamad Khirota Gorgees Yalda Nicolae Tapus Ibrahim Taner Okumus Faculty of Automatic Control and Computer Science Politehnica University of Bucharest Bucharest Romania Soran Technical college Erbil Polytechnic University Erbil Iraq Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey

“The cloud“ points out to servers, the databases and software that run on those servers. The Internet has always been constructed of infrastructure, servers and clients. Clients send their requests to servers, and servers reply, but cloud computing is distinct in the form that cloud servers are not just replying to requests with on-demand processing but they are saving data and running programs instead of the client. Cloud computing is a technology that is crossing a great expansion today. In cloud computing you can dynamically expand resources without knowledge of a new infrastructure, without developing new software or preparing new staff and to access such great technology the only things that are asked for are an Internet connection and an Internet browser. The goal of this survey is to present the different cloud security threats and recognize the proper security mechanism used to reduce them.

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Finite-time robust performance improvement for non-linear systems in the presence of input non-linearity and external disturbance

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IET control Theory and Applications 2023年第6期17卷 672-682页

作者： Wang, Haoping Ghaffari, Valiollah Mobayen, Saleh Bartoszewicz, Andrzej Fekih, Afef Assawinchaichote, Wudhichai School of Automation Nanjing University of Science and Technology Nanjing China Department of Electrical Engineering Persian Gulf University Bushehr Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou Taiwan Institute of Automatic Control Lodz University of Technology Lodz Poland Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA United States Department of Electronic and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

The main focus of this research is on improving the performance of dynamic systems with actuator non-linearities and time-varying disturbances. To this end, using the concept of finite-time stability, a novel observer is presented to estimate the disturbances in systems with input non-linearities. Then, introducing an innovative sliding manifold, a robust observer-based technique is derived to guarantee the finite-time stability of the sliding surface. Hence, the closed-loop system would be stable in the presence of hard non-linearities and time-varying disturbances. The performance of the proposed approach was assessed in using a simulation study of two numerical examples. The obtained results and comparison with a conventional method confirmed the benefits of the suggested approach. © 2022 The Authors. IET control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Closed loop systems

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Bitroute SOME/IP: Implementation of a Scalable and Service Oriented Communication Middleware 45

Bitroute SOME/IP: Implementation of a Scalable and Service O...

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Vujanic, M. Trifunovic, N. Kastelan, I. Kovacevic, B. University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Serbia RT-RK Institute for Computer Based Systems Novi Sad Serbia

ISBN: (纸本)9789532331035

SOME/IP is a communication protocol introduced in automotive industry to enable Service Oriented Architecture which is not possible using traditional automotive protocols such as CAN or FlexRay. A trend emerging in the last years in the Advanced Driver Assistance Systems (ADAS) is that SOME/IP became one of main communication protocols used for communication between safety and performance ECU devices. Currently in the market, including the open-source solutions, there is a set of different SOME/IP implementations that have different audience and combination of characteristics like high royalty costs, available feature set and software solution maturity. This paper presents the Bitroute SOME/IP, a new implementation of the SOME/IP communication protocol with focus on performance and deployment platform independency and compares it with the open-source solution from The Connected Vehicle Systems Alliance (COVESA). © 2022 Croatian Society MIPRO.

关键词： Automotive industry

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Deep Convolutional Neural Networks for Real-Time Human Detection and Tracking on UAVs Embedded Systems

Deep Convolutional Neural Networks for Real-Time Human Detec...

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Mediterranean Conference on control and Automation (MED)

作者： Trandafir-Liviu Serghei Petrișor Valentin Pârvu Mădălina-Oana Serghei Dan Popescu Loretta Ichim Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania Faculty of Aerospace Engineering University Politehnica of Bucharest Bucharest Romania

Human detection for critical missions with unmanned aerial vehicle (UAV) support becomes more and more important in the actual context when tension at borders builds up for an increasing number of countries. Although convolutional neural networks are continuously evolving, the required computational resources pose a great problem when implemented on portable embedded systems such as UAVs, with limited processing power and autonomy. This demand becomes even more drastic when running real-time human detection and tracking. This paper proposes an improved implementation of the YOLOv.7, trained on a custom dataset, for real-time human detection and tracking with confidence scores above 80% on NVIDIA Jetson TX2 neural processing unit equipped on DJI Matrice 100 UAV. The authors created a YOLOv.7 model running independently on an embedded system for real-time human detection and tracking.

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An approach towards Model-To-Model Mapping between AUTOSAR and Android systems 45

An approach towards Model-To-Model Mapping between AUTOSAR a...

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Zlatkovic, Radomir Cabrilo, Vuk Antic, Marija Kovacevic, Branimir University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Serbia RT-RK Institute for Computer Based Systems Novi Sad Serbia

ISBN: (纸本)9789532331035

Every new generation of modern vehicles aims to provide the customers with a higher level of comfort and entertainment services. Consequently, the burden is placed upon the manufacturers to incorporate ever more complex electronic systems in their products and introduce service-based technologies. To meet these demands, service-oriented architecture (SOA) has become an integral part of the Adaptive AUTOSAR as the industry standard. Also, mobile services and applications are natively supported in the new in-vehicle infotainment systems (IVI) which usually run on the Android operating system. As these fundamentally different technologies are incorporated in the vehicles, the developers are facing the challenge of connecting them and exchanging information between the services running in different domains. Service-oriented architectures usually rely on a model-driven engineering approach to facilitate the development of the applications. However, as the complexity of the system grows, the mapping of various metamodels becomes a challenge, as no single standard is used across all domains in the vehicle. This paper provides a possible solution for mapping the already existing AUTOSAR metamodel to an Android Interface Definition Language (AIDL) metamodel. By applying the proposed mapping, it is possible to build applications that require the cooperation of various domains within the vehicle. © 2022 Croatian Society MIPRO.

关键词： Mapping

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PV powered neuromorphic sensors with optical connectivity

PV powered neuromorphic sensors with optical connectivity

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Communications and Networking (BalkanCom), International Balkan Conference on

作者： George-Iulian Uleru Alexandru Barleanu Mircea Hulea Zabih Ghassemlooy Faculty of Automatic Control and Computer Engineering Gheorghe Asachi Technical University of Iasi Iasi Romania Photonics Technology Laboratory Optical Communications Research Group. FEE Northumbria University Newcastle upon Tyne United Kingdom

ISBN: (数字)9798350365955

ISBN: (纸本)9798350365962

The spiking neural networks (SNN) benefits from low power consumption, very good signal-to-noise ratio and the ability to model rigorously the physiology of the biological neural areas. In robotics, the SNN can be used in different applications including motion control where the neural module drives the actuators based on the information from sensors. The most suitable type of sensing devices in biomimetic robotics are the neuromorphic sensors (NS) with spiking output which can include an optical transmitter for wireless connectivity. Considering that the reduced energy consumption is a critical characteristic for the SNN, in this work we evaluate the possibility of using photovoltaic (PV) panels to power the NS with optical output. The focus is on the recently introduced type of NS with integrated force sensing resistor (FSR) that uses a module based on a light emitting diode (LED) to generate optical pulses. We measured the responses of this NS with the load mass when it is powered by a PV panel, and the results show that the NS operates in nominal conditions despite the slight variations of the used supply voltage. Moreover, the NS is able to transmit optical pulses which frequency depends on the load mass.

关键词： Biomedical optical imaging Neuromorphics Robot sensing systems Optical network units Optical receivers Sensors Optical sensors

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Traditional Chinese Medicine Health Status Identification with Graph Attention Network 1

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Fu, Amin Ma, Jishun Wang, Chuansheng Zhou, Changen Li, Zuoyong Teng, Shenghua College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China Department of Automatic Control Technical Polytechnic University of Catalonia Barcelona08034 Spain Research Base of Traditional Chinese Medicine Syndrome Fujian University of Traditional Chinese Medicine Fuzhou350122 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China

ISBN: (数字)9783031200960

ISBN: (纸本)9783031200953

The Traditional Chinese Medicine Health Status Identification plays an important role in TCM diagnosis and prescription recommendation. In this paper, we propose a method of Status Identification via Graph Attention Network, named SIGAT, which captures the complex medical correlation in the symptom-syndrome graph. More specifically, we construct a symptom-syndrome graph in that symptoms are taken as nodes and the edges are connected by syndromes. And we realize automatic induction of symptom to state element classification by using the attention mechanism and perceptron classifier. Finally, we conduct experiments by using hamming loss, coverage, 0/1 error, ranking loss, average precision, macro-F1 score, and micro-F1 score as evaluation metrics. The results demonstrate that the SIGAT model outperforms comparison algorithms on Traditional Chinese Medicine Prescription Dictionary dataset. The case study results suggest that the proposed method is a valuable way to identify the state element. The application of the graph attention network classification algorithm in TCM health status identification is of high precision and methodological feasibility. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

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